Risk Prediction in Patients With Heart Failure With Preserved Ejection Fraction Using Gene Expression Data and Machine Learning

Risk Prediction in Patients With Heart Failure With Preserved Ejection Fraction Using Gene Expression Data and Machine Learning

Heart failure with preserved ejection fraction (HFpEF) has become a major health issue because of its high mortality, high heterogeneity, and poor prognosis. Using genomic data to classify patients into different risk groups is a promising method to facilitate the identification of high-risk groups...

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Bibliographic Details
Main Authors: Liye Zhou, Zhifei Guo, Bijue Wang, Yongqing Wu, Zhi Li, Hongmei Yao, Ruiling Fang, Haitao Yang, Hongyan Cao, Yuehua Cui
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-03-01
Series:Frontiers in Genetics
Subjects:
risk prediction
kernel partial least squares
genetic algorithm
heart failure with preserved ejection fraction
machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2021.652315/full

Internet

https://www.frontiersin.org/articles/10.3389/fgene.2021.652315/full

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